In Silico Analysis of Inhibitors Against the RNA-binding motif 10 (RBM10) Protein in Non-Small Cell Lung Cancer

With other 2 million cases around the globe, lung cancer is perhaps the second most frequence cancer. RMB10 protein is a tumor suppressor protein and helps in controlling cell growth and preventing cells from becoming cancerous. Mutations or dysregulation of these genes can contribute to the development and advancement of lung cancer, such as non-small cell lung cancer (NSCLC). Dysregulation of this protein results in the aberrant RNA processing, leading to tumor growth and metastasis, hence rendering it an exceptional target for drug development. However, due to a highly flexible nature of RBM10, targeting the entire protein is very impractical. Therefore, in the current work we have targeted only the RRM1 segment of the complete RBM10 protein. We hypothesize that inhibitors will bind strongly to the RNA binding region RRM1 domain of the RBM10 protein complex, thereby inhibiting the RBM10 functioning by restricting the RNA binding to the RBM10 protein. We have used in silico simulations to predict ligands that bind strongly to the RRM1 protein. Specifically, molecular docking simulations were used to scan 3154 compounds and best ligands were selected for further analysis. The results are in agreement in our hypothesis since the ligand specifically binds to the active site predicted by the graph neural network. Since it binds to the active site the interactions of the RNA to the RRM1 and hence RBM10 will be inhibited.